Description: Role: Security Data Scientist

Required Technical Skill Set: Cyber Security Data Science, Security Knowledge Graphs (Graph Databases, Ontologies &

- Link Analysis), Data Engineering (BigQuery, Spark, GCP / Azure Data Pipelines), Machine Learning &
- Anomaly Detection, Attack Path Analysis, Python (Pandas, PyTorch, Scikit-Learn, NetworkX), Graph Query Languages (Cypher / Gremlin / SPARQL), Security Telemetry &
- SIEM/SOC Analytics

Experience Range : 7 – 12 Years overall

Location: Hyderabad technical/data science experience (with 3+ years applying machine learning, graph analytics, or data engineering to cyber security/fraud domains)

Must-Have (Candidates must demonstrate depth in core areas and a blend/combination of the following specialisms)

- Cyber Security Data Science &
- ML: Proven experience designing, training, and deploying machine learning models specifically for security use cases (e.g., UEBA, insider threat detection, anomalous authentication patterns, network intrusion, automated threat scoring).
- Security Knowledge Graphs &
- Graph Analytics: Hands-on experience modeling and querying complex security relationships (identities, assets, permissions, attack paths, vulnerabilities) using Graph Databases (Neo4j, Amazon Neptune, Azure Cosmos DB / Gremlin, AWS Neptune, or Memgraph) and graph traversal languages (Cypher, Gremlin, SPARQL).
- Graph Machine Learning &
- Link Analysis: Practical knowledge of graph algorithms (centrality, community detection,



shortest path, PageRank) and Graph Neural Networks (GNNs) or link prediction to uncover hidden relationships and blast radiuses across enterprise security assets.
- Data Engineering &
- Big Data Pipelines: Solid data engineering expertise in designing scalable ETL/ELT pipelines to ingest, normalize, and enrich massive volumes of multi-cloud security telemetry and logs using GCP BigQuery / Dataproc, Azure Synapse / Databricks, Apache Spark, or Kafka.
- Programming &
- Data Science Toolkit: Advanced proficiency in Python and standard data science libraries (Pandas, NumPy, Scikit-Learn, PyTorch / TensorFlow, NetworkX, Pyvis, DGL/PyG).
- Security Domain Knowledge: Solid understanding of cyber security frameworks, threat intelligence feeds (MITRE Telecommunication&CK;, STIX/TAXII), identity access graphs, and cloud asset topologies.

Good-to-Have

- Experience with GenAI / LLM-powered knowledge graph retrieval (GraphRAG, Vector + Graph hybrid indexing, LangChain / LlamaIndex).
- Familiarity with Data Security Posture Management (DSPM), Cloud Security Posture (CSPM), or asset inventory discovery tools.
- Experience working in regulated financial services environments handling sensitive customer and transactional data.
- Relevant certifications in Data Science, Cloud Data Engineering (GCP Professional Data Engineer, Azure Data Scientist / Data Engineer), or Cyber Security (CISSP, GDAT, or equivalent).

📌 IND_Senior Security Engineer (Hyderabad)
🏢 Artech Infosystems
📍 Hyderabad